Data Science Tech Lead Manager, Model Experience

Anthropic•New York City, NY

8d•Hybrid

About The Position

Anthropic is seeking a senior data science leader for Model Experience to help inform the company's mission of building safe and beneficial AI. The role partners strategically with product, engineering, and research leaders to shape model roadmaps, launch decisions, and other high-impact priorities. It focuses on understanding how users experience models and defining success beyond benchmark scores. As a tech lead manager, this person will hire, manage, and develop a data science team; set its agenda; personally lead high-stakes analyses; and establish strong standards for using data in model and product decisions. The role also defines measurement frameworks, sets expectations for experimentation and causal inference, communicates recommendations to senior stakeholders, and builds foundational data practices and analytics infrastructure to support rapid iteration. The position requires a bachelor's degree or an equivalent combination of education, training, and/or experience in a field relevant to the role. Anthropic currently expects staff to work from an office at least 25% of the time under its location-based hybrid policy. The annual salary range is $380,000–$460,000 USD. Anthropic describes itself as a public benefit corporation headquartered in San Francisco and offers competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and office space for collaboration.

Requirements

Extensive data science experience, including leading analytics for a product or research area at significant scale.
At least 3 years managing data science teams, including setting direction, hiring, and developing senior data scientists.
Experience serving as a trusted partner to senior product, research, and business leaders, with examples of changing a roadmap or high-stakes decision.
Strong product sense and business judgment, including the ability to frame the right question and take a position with incomplete information.
Deep expertise in experimental design, causal inference, and statistical modeling at high scale.
Fluency in Python and SQL sufficient to remain hands-on and guide others' technical work.
Clear written and presentation communication skills, including for executive audiences.
Ability to take action and thrive in ambiguous, fast-moving environments by creating clarity and driving progress.
Care for Anthropic's mission of building helpful, honest, and harmless AI.
Bachelor's degree or an equivalent combination of education, training, and/or experience.
A field of study relevant to the role, as demonstrated through coursework, training, or professional experience.

Nice To Haves

Experience with AI/ML products, large language models, or developer tools in the AI/ML ecosystem.
Experience as a tech lead manager or player-coach, balancing hands-on technical work with people management.
Experience building or scaling a data science team in a fast-growing organization.
Experience working closely with Product or Research teams, especially on LLM or AI products.
Comfort working with unstructured data.

Responsibilities

Act as a strategic thought partner to product, engineering, and research leaders, helping shape model roadmap priorities, launch decisions, and major team bets.
Set the data science agenda for Model Experience, choosing where the team can have the greatest impact and what it should deprioritize.
Hire, manage, and develop data scientists, coaching them to shape decisions rather than only answer questions.
Frame important and ambiguous questions about model quality and user experience, assess opportunities, and make clear recommendations, including when they challenge current direction.
Define success measures for Model Experience and establish core metrics and measurement frameworks across external products and internal testing.
Set standards for experimentation and causal inference, including for launches without clean A/B tests, and personally lead the highest-stakes analyses.
Translate complex analyses of model and user behavior into clear narratives and recommendations for senior leaders and cross-functional partners.
Establish foundational data practices and shape the analytics infrastructure needed to support rapid iteration and decision-making.